In this post, we will create a Bayesian convolutional neural network to classify the famous MNIST handwritten digits. This will be a probabilistic model, designed to capture both aleatoric and epistemic uncertainty. You will test the uncertainty quantifications against a corrupted version of the dataset. This is the assignment of lecture "Probabilistic Deep Learning with Tensorflow 2" from Imperial College London.

Aug 26, 2021